code: def data():
      return make_classification(
          n_samples=200,
          n_features=2,
          n_informative=2,
          n_redundant=0,
          n_repeated=0,
          n_clusters_per_class=1,
          n_classes=3,
          weights=[0.1, 0.3, 0.6],
          random_state=0,
      )
  
file_path: imbalanced-learn/imblearn/under_sampling/_prototype_selection/tests/test_neighbourhood_cleaning_rule.py
imports: from collections import Counter
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.utils._testing import assert_array_equal
  from imblearn.under_sampling import EditedNearestNeighbours, NeighbourhoodCleaningRule
label_desc: Use image node_id 1 for calling a global function with example usage: data() and returns: make_classification